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Predatorsidyt/customer-segmentation---Churn-Prediction

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Customer Segmentation: Using unsupervised learning algorithms like K-means, DBSCAN, or hierarchical clustering, you can segment customers based on their purchase behavior, location, and other features. This will help businesses to tailor their marketing strategies to different customer segments effectively.

active 2024-01-08 → 2024-01-19 (UTC)

Complete coverage28,024 / 28,024 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-25 (UTC)
Events
6
Pushes
3
Pull requests
0
Issues
0
Stars
1
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 12 days from 2024-01-08 to 2024-01-19. Pushes: 3 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 1 total, peak 1 in a day.

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  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

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Predatorsidyt3300

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No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.